DBMS > EsgynDB vs. Hazelcast vs. MonetDB vs. WakandaDB

System Properties Comparison EsgynDB vs. Hazelcast vs. MonetDB vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A widely adopted in-memory data grid

A relational database management system that stores data in columns

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

Technical documentation

hazelcast.org/imdg/docs

www.monetdb.org/Documentation

wakanda.github.io/doc

Developer

Esgyn

Hazelcast

MonetDB BV

Wakanda SAS

Initial release

2015

2008

2004

2012

Current release

5.3.6, November 2023

Dec2023 (11.49), December 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

Mozilla Public License 2.0

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

Java

C++, JavaScript

Server operating systems

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

SQL 2003 with some extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Event Listeners, Executor Services

yes, in SQL, C, R

yes

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Replicated Map

none

Source-replica replication available in experimental status

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard

yes

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